Re: [R] extracting coefficients from lmer

From: Dimitris Rizopoulos <dimitris.rizopoulos_at_med.kuleuven.be>
Date: Tue 10 Jan 2006 - 22:05:44 EST

you can use something like:

Vcov <- vcov(lmer.fit, useScale = FALSE) betas <- fixef(lmer.fit)
se <- sqrt(diag(Vcov))
zval <- betas / se
pval <- 2 * pnorm(abs(zval), lower.tail = FALSE) ###############
cbind(betas, se, zval, pval)

I hope it helps.

Best,
Dimitris



Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium

Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://www.med.kuleuven.be/biostat/
     http://www.student.kuleuven.be/~m0390867/dimitris.htm


> Dear R-Helpers,
>
> I want to compare the results of outputs from glmmPQL and lmer
> analyses.
> I could do this if I could extract the coefficients and standard
> errors
> from the summaries of the lmer models. This is easy to do for the
> glmmPQL
> summaries, using
>
>> glmm.fit <- try(glmmPQL(score ~ x*type, random = ~ 1 | subject,
>> data = df,
> family = binomial), TRUE)
>> summary(glmmPQL.fit)$tTable
>
> Linear mixed-effects model fit by maximum likelihood
> Data: df
> AIC BIC logLik
> 1800.477 1840.391 -890.2384
>
> Random effects:
> Formula: ~1 | subject
> (Intercept) Residual
> StdDev: 0.6355517 0.9650671
>
> Variance function:
> Structure: fixed weights
> Formula: ~invwt
> Fixed effects: score ~ x * type
> Value Std.Error DF t-value p-value
> (Intercept) -0.0812834 0.2933314 294 -0.2771043 0.7819
> x1 0.4143072 0.4180624 98 0.9910176 0.3241
> type2 0.8509166 0.4084443 294 2.0833112 0.0381
> type3 0.6691275 0.4024369 294 1.6626894 0.0974
> type4 -0.7830413 0.4123851 294 -1.8988109 0.0586
> x1:type2 1.0643239 0.6791126 294 1.5672274 0.1181
> x1:type3 -0.7533085 0.5674532 294 -1.3275253 0.1854
> x1:type4 -0.0549616 0.5777216 294 -0.0951351 0.9243
> etc.
>
> However, there seems to be no route to extract the corresponding
> information
> from the lmer model:-
>
>> lmer.fit=try(lmer(score~x*type+(1|subject), data=df,
>> family=binomial,
> method='AGQ'),TRUE)
>> summary(lmer.fit)
>
> Generalized linear mixed model fit using AGQ
> Formula: score ~ x * type + (1 | subject)
> Data: df
> Family: binomial(logit link)
> AIC BIC logLik deviance
> 510.2616 550.1762 -245.1308 490.2616
> Random effects:
> Groups Name Variance Std.Dev.
> subject (Intercept) 0.46269 0.68021
> # of obs: 400, groups: subject, 100
>
> Estimated scale (compare to 1) 1.019134
>
> Fixed effects:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) -0.087284 0.300896 -0.29008 0.77175
> x1 0.446289 0.428844 1.04068 0.29803
> type2 0.913571 0.418978 2.18047 0.02922 *
> type3 0.719023 0.412816 1.74175 0.08155 .
> type4 -0.839842 0.423021 -1.98534 0.04711 *
> x1:type2 1.112673 0.696629 1.59722 0.11022
> x1:type3 -0.809599 0.582089 -1.39085 0.16427
> x1:type4 -0.062235 0.592623 -0.10502 0.91636
> etc.
>
>> summary(lmer.fit)$tTable
> NULL
>> names(summary(lmer.fit))
> NULL
>> names(lmer.fit)
> NULL
>> lmer.fit$coef
> NULL
>
> So, then I tried to find out if lmer returns different information.
>> help(lmer)
> This says "see lmer-class" ->
>> help(lmer-class)
> No documentation for 'lmer - class' in specified packages and
> libraries:
> you could try 'help.search("lmer - class")'
>
> So, then I tried
>> help.search('lmer-class')
>
> This returns
> Help files with alias or concept or title matching 'lmer-class'
> using fuzzy
> matching:
> lmer-class(Matrix) Mixed model representations
>
> So, I loaded library Matrix and tried again
>> library(Matrix)
>> help(lmer-class)
> No documentation for 'lmer - class' in specified packages and
> libraries:
> you could try 'help.search("lmer - class")'
>
> If someone could tell me how to extract the Estimates and Std.
> Errors from
> the lmer summary, I'd be very grateful. I would also be very
> grateful if
> someone
> could let me know why the Estimates and Std. Errors from the lmer
> model are
> both
> larger than those from the glmmPQL model.
>
> I am running R 2.2.1 on a Windows XP machine.
>
> Thanks,
>
> Jonathan Williams
>
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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Tue Jan 10 22:27:54 2006

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